- Research, design, develop, and test operating systems-level software, compilers, and network distribution software for massive social data and prediction problems.
- Have industry experience working on a range of ranking, classification, recommendation, and optimization problems, e.g. payment fraud, click-through or conversion rate prediction, click-fraud detection, ads/feed/search ranking, text/sentiment classification, collaborative filtering/recommendation, or spam detection.
- Working on problems of diverse scope, develop highly scalable systems, algorithms and tools leveraging deep learning, data regression, and rules based models.
- Suggest, collect, analyze and synthesize requirements and bottleneck in technology, systems, and tools.
- Demonstrates good judgment to develop solutions that iterate orders of magnitude with a higher efficiency, efficiently leverage orders of magnitude and more data, and explore state-of-the-art deep learning techniques.
- Receiving little instruction from supervisor, code deliverables in tandem with the engineering team.
- Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
- Telecommuting is permitted from anywhere in the U.S.
- Master's degree in Computer Science, Electrical Engineering, Computer Engineering, or related field and 36 months of experience in the job offered or related occupation.
- Experience must include 36 months involving the following:
- 1. Machine Learning Framework(s): PyTorch, MXNet, or Tensorflow
- 2. Machine learning, recommendation systems, computer vision, natural language processing, data mining, or distributed systems
- 3. Translating insights into business recommendations
- 4. Machine learning, recommendation systems, pattern recognition, data mining, or artificial intelligence
- 5. Linux, UNIX, or other *nix-like OS as evidenced by file manipulation, advanced commands, and shell scripting
- 6.Data processing, programming languages, databases, networking, operating systems, computer graphics, or human-computer interaction, AND
- 7. Applying algorithms and core computer science concepts to real world systems as evidenced by recognizing and matching patterns from different areas of computer science in production systems.
Individual pay is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base salary, Meta offers benefits. Learn more about benefits at Meta.